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Results indicate that with zero curated data, OPT-Zero matches state-of-the-art data-dependent methods while exhibiting substantially stronger generalizability, establishing self-play training as a highly scalable paradigm for advancing LLM reasoning in modeling and solving optimization problems.
A novel framework called Multi-Term Fourier Graph Neural Network with Sample Relationship Learning (MTFGN-SRL) is introduced, which considers the sample as a single complete graph and utilize a Fourier Graph Neural Network (FGN) to capture the spatio-temporal information in the frequency domain.
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